Instructions to use ProbeX/Model-J__MAE__model_idx_0726 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__MAE__model_idx_0726 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__MAE__model_idx_0726") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__MAE__model_idx_0726") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0726", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9deec7b02362cd22a0d6ba417526c2271de0752a9d0f7820c59e0ebc2902236f
- Size of remote file:
- 5.37 kB
- SHA256:
- 0601305ebc000ea84f8fefc09efa183ca52a889a134aadf9bae84f9e82172bbb
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